Bridging the gap between human and machine vision

Researchers develop a more robust machine-vision architecture by studying how human vision responds to changing viewpoints of objects.

Kris Brewer | Center for Brains, Minds and Machines | Feb. 11, 2020 | mit
~5 mins   

Tags: center-for-brains-minds-and-machines brain-and-cognitive-sciences machine-learning artificial-intelligence computer-vision research school-of-science computer-science-and-technology

Differences between deep neural networks and human perception

Stimuli that sound or look like gibberish to humans are indistinguishable from naturalistic stimuli to deep networks.

Kenneth I. Blum | Department of Brain and Cognitive Sciences | Dec. 12, 2019 | mit
~7 mins   

Tags: brain-and-cognitive-sciences center-for-brains-minds-and-machines mcgovern-institute research machine-learning artificial-intelligence school-of-science neuroscience

Perception of musical pitch varies across cultures

How people interpret musical notes depends on the types of music they have listened to, researchers find.

Anne Trafton | MIT News Office | Sept. 19, 2019 | mit
~9 mins   

Tags: research brain-and-cognitive-sciences music behavior mcgovern-institute school-of-science national-institutes-of-health-nih neuroscience center-for-brains-minds-and-machines

For better deep neural network vision, just add feedback (loops)

The DiCarlo lab finds that a recurrent architecture helps both artificial intelligence and our brains to better identify objects.

Sabbi Lall | McGovern Institute for Brain Research | April 29, 2019 | mit
~6 mins   

Tags: school-of-science brain-and-cognitive-sciences mcgovern-institute center-for-brains-minds-and-machines artificial-intelligence computer-vision autonomous-vehicles national-science-foundation-nsf research

Recognizing the partially seen | MIT News

Advances in computer vision inspired by human physiological and anatomical constraints are improving pattern completion in machines.

Kris Brewer | Center for Brains, Minds and Machines | Sept. 20, 2018
~4 mins |

Tags:  artificial-intelligence  machine-learning  computer-vision  school-of-science  brain-and-cognitive-sciences  research  computer-modeling  center-for-brains-minds-and-machines  mcgovern-institute

MIT announces leadership of its Quest for Intelligence | MIT News

Faculty from across the Institute tapped to lead new initiative in human and machine intelligence.

MIT News Office | June 11, 2018
~5 mins |

Tags:  artificial-intelligence  machine-learning  algorithms  computer-science-and-technology  research  president-l-rafael-reif  brain-and-cognitive-sciences  electrical-engineering-computer-science-eecs  computer-science-and-artificial-intelligence-laboratory-csail  media-lab  center-for-brains-minds-and-machines  quest-for-intelligence

Computer systems predict objects’ responses to physical forces | MIT News

Results may help explain how humans do the same thing.

Larry Hardesty | MIT News Office | Dec. 13, 2017
~9 mins |

Tags:  research  center-for-brains-minds-and-machines  school-of-engineering  school-of-science  artificial-intelligence  brain-and-cognitive-sciences  computer-modeling  computer-science-and-artificial-intelligence-laboratory-csail  computer-science-and-technology  electrical-engineering-computer-science-eecs  machine-learning

How badly do you want something? Babies can tell | MIT News

Ten-month-old infants determine the value of a goal from how hard someone works to achieve it.

Anne Trafton | MIT News Office | Nov. 23, 2017
~9 mins |

Tags:  research  brain-and-cognitive-sciences  learning  center-for-brains-minds-and-machines  mcgovern-institute  computer-science-and-artificial-intelligence-laboratory-csail  school-of-science  school-of-engineering  national-science-foundation-nsf

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